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Related Experiment Video

Updated: Jun 17, 2026

Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease

Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease

Published on: November 14, 2017

Genetics Analysis Workshop 16 Problem 2: the Framingham Heart Study data.

L Adrienne Cupples¹, Nancy Heard-Costa, Monica Lee

¹Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston Massachusetts 02118, USA. adrienne@bu.edu.

BMC Proceedings

|December 19, 2009

Summary

This summary is machine-generated.

The Framingham Heart Study (FHS) provided rich genetic and longitudinal data for three generations. This resource aids researchers in developing new methods for genome-wide scans and cardiovascular disease risk factor analysis.

Related Experiment Videos

Last Updated: Jun 17, 2026

Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease

Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease

Published on: November 14, 2017

Area of Science:

Genetics
Cardiovascular Disease Research
Biostatistics

Background:

The Framingham Heart Study (FHS) is a long-term observational study initiated in 1948.
Data spans three generations, with repeated measurements for the first two generations.
Includes phenotype and genome-wide genotype data.

Purpose of the Study:

To provide a comprehensive dataset for analyzing cardiovascular disease risk factors.
To facilitate the development and application of new statistical methods for genetic analysis.
To enable the study of genome-wide scans using longitudinal family data.

Main Methods:

Utilized phenotype data including blood pressure, lipids, diabetes, and coronary heart disease incidence.
Incorporated genome-wide genotype data from 550,000 single-nucleotide polymorphisms (SNPs).
Employed longitudinal data collection across three generations.

Main Results:

The dataset serves as a valuable resource for genetic association studies.
Enabled the testing of analytical methods on real-world, complex family data.
Facilitated the exploration of genotype-phenotype relationships over time.

Conclusions:

The FHS data, combined with genome-wide scans, offers a powerful platform for cardiovascular research.
The resource supports advanced statistical genetics and the discovery of novel disease associations.
Promotes methodological innovation in analyzing large-scale, longitudinal genetic datasets.